FungalG

enom

ics

and

Susta

inable

Develo

pm

ent

Gre

gButler

Depart

ment

ofCom

pute

rScie

nce

and

Software

Engin

eering

Centr

efo

rStr

uctu

raland

FunctionalG

enom

ics

Concord

iaUniv

ers

ity,

Montr

eal

www.cs.concordia.ca/~gregb

gregb@cs.concordia.ca

Outlin

e

Genom

ics

Enzym

es

and

Bio

-Pro

cess

ing

for

Sust

ain

able

Develo

pm

ent

Overv

iew

ofth

eFungalG

enom

ics

Pro

ject

Bio

info

rmatics

for

the

FungalG

enom

ics

Pro

ject

Conclu

sion

Bio

logy

—Tra

nscription

and

Tra

nsla

tion

Bio

logy

—Tra

nscription

Regula

tion

Bio

logy

implies

...

...

use

Multip

leSequence

Alignm

ent

(MSA)

MSA

Pro

ble

m:

Giv

en

ase

tofpro

tein

sequences,

and

an

obje

ctive

func-

tion,dete

rmin

eth

eoptim

alalignm

ent

ofth

ese

quences.

Why?

Am

ino

acid

sequence

dete

rmin

es

pro

tein

stru

ctu

re

dete

rmin

es

enzym

efu

nction

Genom

ics

and

Bio

info

rmatics

—Health

Pers

pective

Genom

ics

hig

h-t

hro

ughput,

collecting

or

using

all

genes

Genom

ics

pro

ject:

dete

rmin

efu

llchro

moso

me

sequence,pre

dic

tgenes

EST

Pro

ject:

min

em

RNA,ass

em

ble

into

”unig

enes”

Mic

roarr

ay

Pro

ject:

genom

e-o

n-a

-chip

,st

udy

gene

activity

Expre

ssio

nPro

ject:

splice

gene

into

host

,pro

duce

enzym

e

Enzym

eAss

ay

and

Chara

cte

rization

Pro

ject:

chem

istr

yand

bio

chem

istr

y

Pro

teom

ics,

...

What

isan

Enzym

e?

Enzym

eis

apro

tein

that

cata

lyse

sa

reaction.

What

isan

Enzym

e?

Enzym

es

are

very

specifi

c.

Enzym

es

are

very

effi

cie

nt

cata

lyst

s.

Industr

ialPro

cessin

gofTre

es

Industr

ialUses

ofEnzym

es:

Paper

Industr

ialUses

ofEnzym

es:

Bio

-Eth

anolfrom

Fore

str

yW

aste

Does

Bio

technolo

gy

forSusta

inability

Work

?

OECD

report

on

21

case

studie

s

wid

era

nge

of

indust

rialse

cto

rs:

pharm

aceuticals,

fine

chem

icals,

bulk

chem

icals,fo

od

and

feed,te

xtile

s,pulp

and

paper,

min

era

lsand

energ

y.

inAust

ria,Canada,G

erm

any,

Japan,th

eNeth

erlands,

the

United

Kin

g-

dom

,th

eUnited

Sta

tes

and

South

Afric

a.

“th

eir

use

invariably

leads

tore

duction

inopera

ting

cost

sorcapitalcost

sor

both

”

“New

”bio

-pro

cess

es”

can

subst

antially

reduce

em

issions

and

the

use

of

hazard

ous

raw

mate

rials.”

”T

hey

resu

ltin

fewer

by-p

roducts

,genera

tefe

wer

wast

em

ate

rials

and

consu

me

less

energ

y.”

The

Application

ofBio

technolo

gy

toIn

dust

rialSust

ain

ability,148

pages,

OECD

,Paris

2001

The

FungalGenom

ics

Pro

ject

Identify

use

fulenzym

es

for

indust

rialapplications

secre

ted

by

14

specie

soffu

ngi

by

const

ructing

cD

NA

libra

ries

with

5000

genes

per

specie

s

and

dete

cting

genes

sim

ilar

toknow

nenzym

es

and

by

const

ructing

cD

NA

mic

roarr

ay

for

each

specie

s

and

dete

cting

genes

expre

ssed

under

rela

ted

conditio

ns

Chara

cte

rize

sele

cte

denzym

es

FungalSpecie

s

Exte

rnalConte

xt

ofFungalG

enom

ics

Pro

ject

Exte

rnalConte

xt

—Public

Data

The

FungalGenom

ics

Pro

ject

What

isBio

info

rmatics?

To

store

,org

anize

&analy

ze

bio

logic

aldata

Models

—m

ath

em

atical,

statist

ical,

physical

Alg

orith

ms

—st

ring,tr

ee,gra

ph,patt

ern

s

Data

base

technolo

gy

Work

flow

and

com

puta

tionalgrids

Inte

llig

ent

reaso

nin

g—

expert

syst

em

s,agents

Web

access

,visualization,usa

bility

Rapid

syst

em

develo

pm

ent

and

evolu

tion

Bio

info

rmatics

forth

eFungalGenom

ics

Pro

ject

Aim

s

ensu

rehig

h-q

uality

experim

enta

ldata

iscollecte

d

know

quality

,confidence,pro

venance

ofdata

auto

mate

data

analy

sis

&re

port

genera

tion

Concern

s

Hid

eth

ete

chnolo

gy,

Do

the

scie

nce

Confidence

inre

sults/

inte

rpre

tation

Fle

xib

ility,

stayin

gahead

ofth

ecurv

e

Bang

for

the

buck

com

puta

tionalre

sourc

es

can

be

huge

Bio

info

rmatics

forth

eFungalGenom

ics

Pro

ject

Bio

info

rmatics

—Curr

ent

Needs

•M

ate

rials

Tra

ckin

g

•D

ata

Collection

•Q

uality

Contr

olofD

ata

and

Pro

cess

•Analy

sis

ofSequences

—Auto

mate

dAnnota

tion

•Analy

sis

ofTarg

et

Sequences

—M

anualCura

tion

•Analy

sis

ofM

icro

arr

ay

Data

—Basic

Expre

ssio

n

Bio

info

rmatics

—Futu

reNeeds

•Analy

sis

ofM

icro

arr

ay

Data

—Pro

filing

•Analy

sis

ofM

icro

arr

ay

Data

—In

tegra

ting

oth

er

Evid

ence

•Enzym

eFam

ilie

s—

Phylo

geny,

Multip

leAlignm

ent,

Cla

ssifi

ers

•Enzym

eFam

ilie

s—

Pre

dic

ting

Kin

etics

Bio

info

rmatics

Pla

tform

Bio

info

rmatics

—Housekeepin

gTasks

Mate

rials

Tra

ckin

g

identify

(bar

code

labels)

and

record

mate

rials

know

location

ofall

rele

vant

physicalm

ate

rials

know

mappin

gs

cause

dby

physicaltr

ansf

er

ofm

ate

rials

Data

Collection

keep

all

data

secure

and

access

ible

know

quality

and

pro

venance

ofall

data

support

analy

sis

and

inte

rpre

tation

ofdata

Quality

Contr

ol

know

the

quality

ofdata

pro

vid

ere

port

sto

monitor

quality

ofla

bpro

cess

es

ass

ist

india

gnosis

ofpro

ble

ms

with

lab

pro

cess

es

Bio

info

rmatics

—Analysis

Tasks

Sequence

Analysis

dete

rmin

ehig

h-q

uality

sequence

segm

ent

...

base

call

quality

,re

move

conta

min

ants

,tr

im

ass

em

ble

EST

sin

tounig

enes

Sequence

Annota

tion

sim

ilarity

again

stknow

nnucle

icand

pro

tein

sequences

...

esp

ecia

lly

again

stta

rgett

ed

enzym

efa

milie

s

searc

hfo

rpro

tein

motifs

and

dom

ain

s

isit

secre

ted

enzym

e?

oth

er

localization

info

?

cla

ssify

toG

ene

Onto

logy

cate

gory

Micro

array

Data

Analysis

norm

alize:

QC

dete

rmin

es

bad

spots

and

dynam

icra

nge

set

thre

shold

for

signifi

cant

expre

ssio

nle

vels

dete

rmin

ehig

hly

expre

ssed

genes

Conclu

sio

n

Bio

-Pro

cess

ing

using

fungalenzym

es

isa

way

tosu

stain

ability.

Bio

info

rmatics

for

findin

gand

unders

tandin

gfu

ngalenzym

es

isa

rich,

challengin

gare

afo

rin

terd

iscip

linary

rese

arc

h

Long-t

erm

Challenges

inBio

info

rmatics:

•Enzym

eFam

ily

Data

—be

able

topre

dic

tkin

etics

•Scie

ntific

Litera

ture

—be

able

tom

ine

know

ledge

•G

ene

Expre

ssio

nD

ata

—be

able

topre

dic

tfu

nction

—be

able

topre

dic

tre

gula

tion

•...

Syst

em

sBio

logy

Excitin

gtim

es

ahead

!!!

Acknowle

dgem

ents

Thank

you!

Questions?